Data Science Engineer 3

Business Environment

Joining Amadeus means shaping the technology that keeps airports and airlines moving for millions of travelers every day. Our department, Airport and Airline Operations (AirOps), is the leading industry platform in airline and airport operations, delivering seamless and personalized passenger experience, an optimized airport operation, and automated disruption resolution between airlines, airports, border, and air traffic control.

Within AirOps Engineering in Bangalore (TRU-AOP-ENG), the FBR team [Flight Management, Baggage Reconciliation and Ramp operations] works closely with engineering, product and data colleagues across Amadeus sites worldwide. It delivers solutions for efficient and optimized airport and airline operations.

In FBR you will work on Data analytics solutions that has a visible impact on airline and airport operations.

Summary of the Role

As a Data Scientist in FBR, you will develop data science, AI/ML and analytics applications as part of a team building cloud-native solutions that optimize operations for airports and airlines worldwide. Working in a multidisciplinary team, you will manage data science initiatives from research through to production and make sure every solution delivers measurable value. You will work autonomously within defined processes and act as a technical reference for the team, combining statistical rigor with a clear focus on business outcomes.

What We Offer

·       The opportunity to apply data science to real-world airline and airport operations at global scale.

·       A multidisciplinary team and a clear Individual Contributor career path in Data Science.

·       Modern cloud data and ML tooling on the Azure stack.

Your Main Responsibilities

·       Partner with Product Owners and business stakeholders to identify, curate and prioritize high-value data science use cases.

·       Own the full lifecycle of data science projects, from problem framing and exploration to production, anticipating cross-team dependencies and risks.

·       Translate complex analytics into clear insights and recommendations for non-technical stakeholders, with a focus on ROI and strategic value.

·       Act as a technical reference for the team, guiding junior data scientists on modeling choices and coding standards through code reviews and mentoring.

·       Share knowledge across the data science community and promote best practices in experimentation, modeling and reproducibility.

·       Stay current with advances in statistical learning, machine learning and Generative AI, and bring forward ideas that drive innovation.

·       Work within Agile/SAFe ways of working and adapt to evolving, customer-driven priorities.

Technical Responsibilities

·       Design and build ML solutions using advanced statistical learning and pattern recognition, including regression, classification, clustering, time-series forecasting and NLP.

·       Develop predictive and optimization models from structured and unstructured data, supported by robust feature engineering.

·       Design experiments, A/B tests and causal analyses to measure the real impact of models.

·       Run the end-to-end ML lifecycle on the Azure stack (Azure ML, Storage, Databricks): data preparation, training, validation, deployment and monitoring.

·       Apply MLOps practices, including CI/CD for ML, experiment tracking, model versioning and reproducibility, and integrate models into production data pipelines.

·       Define evaluation metrics, tune and monitor models for drift, and troubleshoot production issues.

·       Safeguard data quality, model explain-ability and Responsible AI, in line with GDPR and data privacy rules.

·       Apply Generative AI and LLMs where they add clear value, alongside classical statistical and ML methods.

Stakeholder Collaboration & Influence

·       Work closely with Product Owners, Data Engineers and cross-functional teams to translate business problems into data-driven solutions.

·       Communicate insights, model outcomes and technical decisions clearly to any audience.

·       Influence product and operational decisions with evidence and data-backed recommendations.

·       Collaborate effectively in a multi-cultural, global organization.

About the Ideal Candidate

Must have

·       Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics or a related field.

·       6+ years of hands-on experience in data science or ML, including models in production.

·       Deep understanding of statistical learning, probability, data modeling and time-series forecasting.

·       Strong Python skills with modern data manipulation and ML frameworks (for example Pandas or Polars, Scikit-learn, TensorFlow or PyTorch) and git.

·       Experience with cloud platforms (Azure preferred; AWS or GCP considered) and MLOps practices.

·       Experience working with large datasets and distributed computing.

·       Working knowledge of Generative AI and its practical applications.

Nice to have

·       Aviation, airline or airport operations domain experience, for example flight delay prediction, aircraft turnaround or passenger flow forecasting.

·       Operations research and optimization techniques.

·       Hands-on experience with Spark/PySpark, MLflow and Polars.

·       Azure certifications, such as Azure Data Scientist Associate.

·       Publications, conference talks or a competitive data science track record (for example Kaggle).

Soft skills

·       Bridges technical findings and business outcomes, and tells a clear story with data.

·       Delivers high-quality work with minimal supervision and works autonomously within defined processes.

·       Growth mindset, strong problem-solving skills and sound judgement in ambiguous situations.

Excellent communication and comfort in a multi-cultural, global, custo

Diversity & Inclusion

Amadeus aspires to be a leader in Diversity and Inclusion in the tech industry, enabling every employee to reach their full potential by fostering a culture of belonging and fair treatment, attracting the best talent from all backgrounds, and as a role model for an inclusive employee experience.  

Amadeus is an equal opportunity employer and committed to an accessible recruitment process. All qualified applicants will receive consideration for employment without regard to gender, race, ethnicity, sexual orientation, age, beliefs, disability or any other characteristics protected by law.

Be aware of recruitment scams

Amadeus Group never charges fees, requests payment, or asks for financial information during recruitment. All legitimate opportunities are communicated solely through official Amadeus channels, including our careers website. Any payment request or outreach via unofficial platforms (e.g., WhatsApp, Telegram) should be treated as fraudulent.